Computer-assisted instruction was first used in education
and training during the 1950s. Early work was done by IBM and such people as
Gordon Pask, and O.M. Moore, but CAI grew rapidly in the 1960s when federal
funding for research and development in education and industrial laboratories
was implemented. The U.S. Government wanted to determine the possible effectiveness
of computer-assisted instruction, so they developed two competing companies,
(Control Data Corporation and Mitre Corporation) who came up with the PLATO
and TICCIT projects. Despite money and research, by the mid seventies it was
apparent that CAI was not going to be the success that people had believed.
Some of the reasons are: CAI had been oversold and could not deliver, lack of
support from certain sectors, technical problems in implementation, lack of
quality software, and high cost. Computer-assisted instruction was very much
drill-and-practice - controlled by the program developer rather than the learner.
Little branching of instruction was implemented although TICCIT did allow the
learner to determine the sequence of instruction or to skip certain topics.

Contract Learning

Contract learning involves the use of contingency contracts,
which define the terminal behavior the student is to achieve and conditions
for achievement and consequences for completion or non-completion of the assigned
task(s). The contingency contract is mutually agreed upon by teacher and student
after negotiations. Contract learning is often used in open educational systems
in which students from various grade levels share in learning activities.

Contract learning can also be useful in a college setting.
According to Knowles, (1991, p. 39) "Contract learning is, in essence,
an alternative way of structuring a learning experience: It replaces a content
plan with a process plan." For more information on the concept of contract
learning and adult learning theory, visit http://www.msu.edu/user/coddejos/contract.htm.

Codde, J. R. (1996). Using learning contracts in the
college classroom. Retrieved August 19, 2002, from Michigan State University,
Educational Technology Certificate Program Web site: http://www.msu.edu/user/coddejos/contract.htm

Similar to programmed learning and teaching machines individualized instruction
began in the early 1900s, and was revived in the 1960s. The Keller Plan, Individually
Prescribed Instruction, Program for Learning in Accordance with Needs, and Individually
Guided Education are all examples of individualized instruction in the U.S.
(Saettler, 1990).

Programmed Instruction

After experimental use of programmed instruction in the 1920s and 1930s, B.
F. Skinner and J.G. Holland first used programmed instruction in behavioral
psychology courses at Harvard in the late 1950s. Use of programmed instruction
appeared in elementary and secondary schools around the same time. Much of the
programmed instruction in American schools was used with individuals or small
groups of students and was more often used in junior high schools than senior
or elementary schools (Saettler, 1990). Early use of programmed instruction
tended to concentrate on the development of hardware rather than course content.
Concerned developers moved away from hardware development to programs based
on analysis of learning and instruction based on learning theory. Despite these
changes, programmed learning died out in the later part of the 1960s because
it did not appear to live up to its original claims (Saettler, 1990).

System Approach

The systems approach developed out of the 1950s and 1960s focus on language
laboratories, teaching machines, programmed instruction, multimedia presentations
and the use of the computer in instruction. Most systems approaches are similar
to computer flow charts with steps that the designer moves through during the
development of instruction. Rooted in the military and business world, the systems
approach involved setting goals and objectives, analyzing resources, devising
a plan of action and continuous evaluation/modification of the program. (Saettler,
1990)

Collins & Stevens
Inquiry Teaching Model

Collins' Cognitive Theory of Inquiry Teaching is a prescriptive model, primarily
Socratic in nature, meaning that it relies upon a dialectic process of discussion,
questions and answers that occurs between the learner and instructor. The process
is guided in order to reach the predetermined objectives, which are described
in this theory as teacher goals and subgoals. Ultimately, the learners will
discover "how to learn".

Teacher goals and subgoals is one of three main portions of Collins' theory.
The second is the strategies used to realize said goals and subgoals and the
third is the control structure for selecting and pursuing the different goals
and subgoals.

This model represents information processing as a computer model. Information
processing easily relates to computer input-process-output. Processing information
involves subroutines or procedures. Subroutines are performed in a hierarchical
manner to complete tasks. Flow of control can be diagrammed. Logic Theorist
was a computer program by Newell, Shaw and Simon (1955-60) used to simulate
the human process of solving theorems in symbolic language. At the same time
MIT, had a pattern recognition program.

There have been many computer models for human information processing. Two
types of information processing models are those dealing with simulation, or
step by step, and those that are dealing with artificial intelligence and are
task driven. Logic Theorist emulated six human characteristics of problem-solving
behavior.

John M. Keller proposed four conditions that must be met for a learner to be
motivated to learn. Attention, relevance, confidence, and satisfaction (ARCS)
are the conditions that, when integrated, motivate someone to learn. Moreover,
Keller suggests that the ARCS conditions occur as a sequential process (Driscoll,
1993, p. 312). The conditions should be sustained to keep the learner interested
in the topic. Once a learnerís attention is lost, motivation is lost, and learning
does not occur. Shneiderman (1998, p. 25) states that "memorable educational
experiences are enriching, joyful, and transformational." Motivation theory
argues that relevant phenomena fulfill personal needs or goals, which enhances
effort and performance (Means, Jonassen, & Dwyer, 1997). How then can one ensure
that the ARCS model remain active? The key is to vary the conditions to engage
the learner. Because each component of Kellerís ARCS model builds upon the next
model, the instructor should keep the four components in mind when designing
instruction.

CDT specifies how to design instruction for any cognitive domain. CDT provides
the basis for the lesson design in the TICCIT computer based learning system
(Merrill, 1980). It also was the basis for the Instructional Quality Profile,
a quality control tool for instructional materials (Merrill, Reigeluth & Faust,
1979). Fo example, if we were designing a complete lesson on equilateral triangles
according to CDT, it would have the following minimum components:

If the generality was presented by an explanation or illustration, followed
by practice examples, this would be an expository strategy (EG, Eeg). On the
other hand, if the students were required to discover the generality on the
basis of practice examples, this would be an inquisitory strategy (IG, Ieg).

Reg Revans is considered the architect of action learning. Inglis (1994) defined
AL as "a process which brings people together to find solutions to problems
and, in doing so, develops both the individuals and the organization" (p.
3). According to Spence (1998), Revans loosely defined action learning as the
process of learning "from and with peers while tackling real problems (O'Neil
and Marsick 1994)" (p. 1). However, Revans (1980) also says that it is
not just project work, job rotation, case studies or business games. According
to Inglish (1994), action learning differs from these other methodologies in
the following ways.

Learning is centered around the need to find a solution to a real
problem.

Learning is voluntary and learner driven.

Individual development is as important as finding the solution to the problem.

Action learning is a highly visible, social process, which may lead to organizational
change.

Action learning takes time. As originally envisioned, an action learning
program would take 4-9 months, excluding implementation. (Spence, 1998, p.1)

Problem, set, client, set advisor, and process are the basic elements of action
learning. The following is a brief explanation of each element (Spence, 1998).

Problem - The problem should be non-technical in nature and deal
with either strategic or tactical issues. The outcome of the problem solutions
must matter to the participants. Participants within a set may work on the
same problem or different problems.

Set - A set of four to six action learners that solve the problem
together. Set members should be competent and committed and come have a range
of expertise.

Client - The owner of the problem. May be a set member or sponsoring
organization.

Set Advisor - The group facilitator. The set advisor explains the
action learning process and builds appropriate interpersonal skills. This
person also maintains open communication with the client. As the action learning
progresses, set members may take on some of these responsibilities.

Process - Observation of the problem, reflection and hypothesis forming
and action.

Action learning has been applied in many areas of adult education such as nursing
education and human resource development graduate programs.

Inglis, S. (1994). Making the Most of Action Learning. Aldershot, England:
Gower.

Spence, J. (1998). Practice application brief: Action learning for individual
and organizational development [Electronic version]. (Developed with funding
from the Office of Educational Research and Improvement, National Library of
Education, U.S. Department of Education, under Contract No. RR93002001). Retrieved
August 24, 2002, from http://ericacve.org/docs/pab00009.htm

Anchored
Instruction

Anchored instruction is a major paradigm for technology-based learning that
has been developed by Cognition & Technology Group at Vanderbilt (CTGV) under
the leadership of John Bransford. While many people have contributed to the
theory and research of anchored instruction, Bransford is the principal spokesperson
and hence the theory is attributed to him.

The initial focus of the work was on the development of interactive videodisc
tools that encouraged students and teachers to pose and solve complex, realistic
problems. The video materials serve as "anchors" (macro-contexts) for all subsequent
learning an d instruction. As explained by CTGV (1993, p52): "The design of
these anchors was quite different from the design of videos that were typically
used in education...our goal was to create interesting, realistic contexts that
encouraged the active construct ion of knowledge by l earners. Our anchors were
stories rather than lectures and were designed to be explored by students and
teachers. " The use of interactive videodisc technology makes it possible for
students to easily explore the content.

Anchored instruction is closely related to the situated learning framework
(see CTGV, 1990, 1993) and also to the Cognitive Flexibility theory in its emphasis
on the use of technology-based learning.

Authentic learning refers to the idea that learners should be presented to
problems that are realistic situations and found in everyday applications of
knowledge (Smith & Ragan, 1999). Authentic learning is the type of learning
promoted by anchored instruction, in which
instruction is "anchored" in a realistic problem situation (Cognition
and Technology Group, 1990).

Young (1993), recommends the following test of "authenticity." Learning
situations should include some of the characteristics of real-life problem solving,
including ill-structured complex goals. There should also be an opportunity
to distinguish between relevant and irrelevant information. Finding and defining
problems as well as solving them should be a generative process. Finally, students
should engage in collaborative activities in which they draw upon their beliefs
and values.

Case-based learning using case studies to present learners with a realistic
situation and require them to respond as the person who must solve a problem
(Smith & Ragan, 1999). In order to solve problems, learners select and manipulate
several principles. According to Hudspeth and Knirk (1989),

A complete case describes an entire situation and includes background information,
the actions and reactions of persons involved, the solution, and the possible
consequences of the actions taken. Case materials should have enough background
information and detail to that they are readable and believable (p. 31).

Case-based learning is appropriate for learning to problem solve when there
is no one correct solution, particularly with more complex ill-structured problems
(Smith & Ragan, 1999). Case studies can be written so that learners use
more cognitive strategies as they proceed through increasing levels of instruction.
Cases were traditionally used in professional education to teach decision making
skills, such as the Harvard Business School case approach. Use of case-based
studies has also become widespread in the field of medical education.

The focus of this learning-through-guided-experience is on cognitive and metacognitive
skills, rather than on the physical skills and processes of traditional apprenticeships.
Applying apprenticeship methods to largely cognitive skills requires the externalization
of processes that are usually carried out internally. Observing the processes
by which an expert listener or reader thinks and practices these skills can
teach students to learn on their own more skillfully (Collins, Brown, Newman,
1989, p. 457-548). This method includes:

Modeling - involves an expert's carrying out a task so that student
can observe and build a conceptual model of the processes that are required
to accomplish the task. For example, a teacher might model the reading process
by reading aloud in one voice, while verbalizing her thought processes (summarize
what she just read, what she thinks might happen next) in another voice.

Coaching - consists of observing students while they carry out a
task and offering hints, feedback, modeling, reminders, etc.

Articulation - includes any method of getting students to articulate
their knowledge, reasoning, or problem-solving processes.

Reflection - enables students to compare their own problem-solving
processes with those of an expert or another student.

Exploration - involves pushing students into a mode of problem solving
on their own. Forcing them to do exploration is critical, if they are to learn
how to frame questions or problems that are interesting and that they can
solve (Collins, Brown, Newman, 1989, 481-482).

Cognitive Flexibility
Hypertext

Cognitive Flexibility Hypertext (CFH) is a hypermedia learning environment
that provides users with several nonlinear paths of traversing content through
the use of cases, themes, and multiple perspectives. A CFH supports exploration
of an ill-structured (ill-defined) knowledge domain through multiple representations
of the content, promoting flexible knowledge acquisition to enhance transfer
to real-world contexts (Jonassen, Dyer, Peters, Robinson, Harvey, King and Loughner,
1997). The WWW is an ideal medium for designing CFH due to its hyperlinking
feature and access to widespread resources that add richness to content.

Collaborative
Learning

Collaborative learning, also called cooperative learning, is heavily emphasized
in most constructivist approaches (Roblyer, Edwards, & Havriluk, 1996).
Actually, students working in groups to solve problems achieves many goals that
supporters of both constructivism and directed instruction consider to be important.
The CTGV finds that collaborative learning is the best way to promote generative
learning.

Perkins (1991) finds that collaborative learning demonstrates the notion of
distributive intelligence, which states that accomplishment is not a function
of one person, but rather a group in which each contributes to the achievement
of desired goals. Cooperative learning is an ideal way for students to learn
the skills that extend beyond the classroom of sharing responsibility and working
together toward common goals. According to Driscoll (2000), collaboration also
provides students with a way to understand point of view outside their own.
Advances in technology over the past several years have made computer-supported
collaborative learning possible. Web-based technologies can make thinking more
visible through virtual access to knowledge experts.

Communities of Practice include learners and instructors who interact with
one another and other experts via virtual spaces, to build a reciprocal interchange
of ideas, data, and opinions. Transformative styles of communication are characteristic,
where the contributor, participator and the lurker or receiver, are "changed"
as they share in the goal of learning and knowledge generation and application
(Wilson & Cole, 1996).

Computer-Supported Intentional
Learning Environments (CSILEs)

Essentially, CSILE is a type of computer conference in which learners create
communal databases entirely through person-to-group rather than person-to-person
communication. CSILE is a collective knowledge building effort that requires
students to do planning, goal setting and problem solving. CSILEs are based
on a specific environment developed at the Ontario Institute for Studies in
Education.

Discovery Learning

Discovery learning has various definitions. At one end of the spectrum we find
discovery learning in its simplest form. The tools and information needed to
solve a problem or learn a concept are provided and the learner "makes sense"
of them. Another definition is discovery learning as experimentation with some
extrinsic intervention -- clues, coaching, and a framework to help learners
get to a reasonable conclusion. At the other end of the continuum is the expository
teaching model of discovery learning where the learner "discovers" what the
teacher decides he is to discover using a process prescribed by the teacher.

Distributed Learning is when learning is distributed across space, time, and
various media. When telecommunications media is utilized, distributed learning
refers to off-site learning environments where learners complete courses and
programs at home or work by communicating with faculty and other students through
e-mail, electronic forums, videoconferences, and other forms computer-mediated
communication and Internet and Web-based technologies. Distributed learning
environments "result in a diffuse sense of cognition - where what is "known"
lies in the interaction between individuals and artifacts, such as computers
and other technological devices (Dabbagh & Bannan-Ritland, in preparation).

Epistemic games are a formalized structure learning communities use to create
knowledge. Conventions are set that represent defined cultural patterns or forms.
Working together to generate these forms is called participating in epistemic
games. The game involves creating rules or conventions to be followed in generating
a given epistemic form. The products of working together are called epistemic
forms. "Completed" forms contain new knowledge and adhere to defined
structures accepted by the community (Collins & Ferguson, 1993; Morrison
& Collins, in press).

Generative
learning

Generative learning is a learning process in
which learners are given an overall problem and are asked to generate sub-problems,
subgoals, and strategies in order to achieve the larger task (Duffy & Jonassen,
1992). Generative learning strategies can be divided into four major stages:
(1) recalling information from long-term memory; (2) integrating new knowledge
with prior knowledge; (3) relating prior knowledge to new concepts and ideas
in a meaningful way; and (4) connecting new materials to information or ideas
already in the learner's mind (Generative Learning, 2000). Using this strategy,
a learner relates new ideas to prior knowledge in order to provide meaning to
the new material (Ryder, 1998).

Goal-Based Scenarios
(GBSs)

GBSs offer learners the opportunity to role-play from a certain "character's"
perspective or point of view. Their "goal" is for the learner to accomplish
a mission or task associated with their role in the scenario. In order to achieve
this goal, the learner needs to acquire particular skills and knowledge. This
is where and when learning takes place. A GBS, therefore, serves both, to motivate
learners, and to give them the opportunity to "learn by doing." "As
long as a goal is of inherent interest to learners, and the skills needed to
accomplish those goals are the targeted learning outcomes, [we] have a match
and a workable GBS (Naidu, 2001, p.2)."

A designer of a GBS tends to look at it from the top-down. What drives the
design of a GBS is the set of target skills the designer wishes the student
to gain in the GBS. A student, on the other hand, tends to look at a GBS from
the bottom-up. What drives a student is the context and structure of the activities
the GBS offers.

Inquiry-based
Learning

Inquiry-based learning is an approach to instruction that engages students
in investigations to satisfy curiosities. Curiosities are satisfied when individuals
construct mental frameworks that adequately explain their experiences (Haury,
1993). The learner's involvement in the learning content fosters skills and
attitudes that permit the learner to seek resolutions to questions and issues
while constructing new and meaningful knowledge (Inquiry-based Learning: Explanation,
2001, April).

Microworlds/Simulations

In microworlds, students test 'What do you think will happen if ?' questions
in " constrained problem spaces that resemble existing problems in
the real world (Jonassen, 1996, p.237)." Learners generate hypotheses as
they use their knowledge and skill to guess what will happen, try out those
guesses, and reformulate them based on the results of their actions within the
microworld. Microworlds provide the learner with the observation and manipulation
tools necessary to explore and test. The key idea behind microworlds is creating
an environment in which students explore the ideas being learned (Jonassen,
1996).

Simulations are similar to microworlds in that they are experiential and model
reality. Simulations " range from models that mirror the simplified
essence of reality to elaborate synthetic environments with immersion interfaces
that place students inside alternate virtual worlds (Dede, 1996, p.14)."
Microworlds differ from simulations in that microworlds are structured to match
the user's cognitive level so that it is appropriate to the users needs and
level of experience (Rieber, 1992).

MOOs and MUDs

MOO is an acronym for MUD, Object-Oriented. MUD stands for Multi-user Dimension,
or Dungeon, reflecting its origin as a form of the Dungeons and Dragons game
developed for multi-users on the Internet. "In Web-based learning, simulated
role portrayal can be facilitated through Multi-User Dialogue (MUD) environments,
in which instructors create a multi-user space with a central theme, characters
and artifacts (Khan, 2001, p.81, in Walker, 1997)."

Most MUDs still retain this game-like atmosphere, with players earning levels
often by shooting and killing other players. MOOs, however, developed as more
social spaces, lending themselves readily to use as a virtual classroom, or
as spaces for conferences and meetings.

PBL engages the learner in a problem-solving activity. In this process, instruction
begins with a problem to be solved rather than content to be mastered (Hsiao,
1996). Students are introduced to a real-world problem and are encouraged to
dive into it, construct their own understanding of the situation, and eventually
find a solution (Grabowski, Koszalka, & Mccarth, 1998). Major goals of PBL
are to help students develop collaborative learning skills, reasoning skills,
and self-directed learning strategies (Hsiao, 1996).

Five Strategies for Using PBL:

The Problem as a Guide - The problem is presented in order to gain
attention prior to presenting the lesson.

The Problem as an Integrator or Test - The problem is presented after
readings are completed and/or discussed -- these are used to check for understanding.

The Problem as an Example - The problem is integrated into the material
in order to illustrate a particular principle, concept or procedure.

The Problem as a Vehicle for Process - The problem is used to promote
critical thinking whereby the analysis of how to solve it becomes a lesson
in itself.

The Problem as a Stimulus for Authentic Activity - The problem is
used to develop skills necessary to solve it and other problems -- skills
can include physical skills, recall of prior knowledge, and metacognitive
skills related to the problem solving process. A form of authentic assessment
of the skills and activity necessary in the content domain (Duffy & Cunningham,
1996, p.190).

REALs

Rich Environments for Active Learning. Based on constructivist ideas, REALs
involve students in constantly shaping and reshaping knowledge constructed through
their learning experiences. REALs may be implemented through cooperative learning,
generative learning, student centered learning, and problem based learning (Schott).

Grabinger and Dunlap (1995) used the term to summarize the literature on constructivist
learning theory and its five instructional design implications. Learning is
active knowledge construction by learners, learners gaining knowledge in realistic
contexts and the social negotiation of learning. Thus, learning environments
should be characterized by five themes (Bostock, 1998, par. 14):

Palincsar (1986) describes the concept of reciprocal teaching: Reciprocal teaching
refers to an instructional activity that takes place in the form of a dialogue
between teachers and students regarding segments of text. The dialogue is structured
by the use of four strategies: summarizing, question generating, clarifying,
and predicting. The teacher and students take turns assuming the role of teacher
in leading this dialogue. Purpose: The purpose of reciprocal teaching is to
facilitate a group effort between teacher and students as well as among students
in the task of bringing meaning to the text.

Lave argues that learning as it normally occurs is a function of the activity,
context and culture in which it occurs (i.e., it is situated). This contrasts
with most classroom learning activities which involve knowledge which is abstract
and out of context. Social interaction is a critical component of situated learning
-- learners become involved in a "community of practice" which embodies certain
beliefs and behaviors to be acquired. As the beginner or newcomer moves from
the periphery of this community to its center, they become more active and engaged
within the culture and hence assume the role of expert or old-timer. Furthermore,
situated learning is usually unintentional rather than deliberate. These ideas
are what Lave & Wenger (1991) call the process of "legitimate peripheral participation."

Other researchers have further developed the theory of situated learning. Brown,
Collins & Duguid (1989) emphasize the idea of cognitive apprenticeship: "Cognitive
apprenticeship supports learning in a domain by enabling students to acquire,
develop and use cognitive tools in authentic domain activity. Learning, both
outside and inside school, advances through collaborative social interaction
and the social construction of knowledge." Brown et al. also emphasize the need
for a new epistemology for learning -- one that emphasizes active perception
over concepts and representation. Suchman (1988) explores the situated learning
framework in the context of artificial intelligence.

Situated learning has antecedents in the work of Gibson (theory of affordances)
and Vygotsky (social learning). In addition, the theory of Schoenfeld on mathematical
problem solving embodies some of the critical elements of situated learning
framework.

A WebQuest is "an inquiry-oriented activity in which some or all of the
information that students interact with comes from resources on the Internet"
(Goldstein, 1997, para. 1). There are two types of WebQuests:

Short term WebQuest - Lasts one to three periods or days and its goal
is basic knowledge acquisition. A good short term WebQuest will also include
some type of subject integration.

Long term WebQuest - Takes between one week and on month to complete.
A well planned long term WebQuest involves "extending and refining knowledge"
(Goldstein, 1997, Types of WebQuests).